Excess

evals_data_df <- tibble::tribble(_score,course,_min,max,_role,order,~ob, 2,“POLI 618”,1,5,“TA”,1,1, 3,“POLI 618”,1,5,“TA”,1,2, 5,“POLI 618”,1,5,“TA”,1,3, 5,“POLI 618”,1,5,“TA”,1,4, 5,“POLI 618”,1,5,“TA”,1,5, 5,“POLI 618”,1,5,“TA”,1,6, 5,“POLI 618”,1,5,“TA”,1,7, 5,“POLI 618”,1,5,“TA”,1,8, 5,“POLI 618”,1,5,“TA”,1,9, 4,“POLI 666”,1,5,“TA”,2,10, 5,“POLI 666”,1,5,“TA”,2,11, 5,“POLI 666”,1,5,“TA”,2,12, 5,“POLI 666”,1,5,“TA”,2,13, 5,“POLI 666”,1,5,“TA”,2,14)

df_list <- list()

iterate <- function(k){

For loop to create and accumulate dataframes

for (i in 1:nrow(evals_data_df)) { # Subset the dataframe up to the ith row df_subset <- evals_data_df[1:i, ] |> filter(course == k)

# Add a column for the sample number df_subset <- df_subset %>% mutate(sample = i)

# Assign to a new variable with dynamic names df_list[[paste0(“df”, i)]] <- df_subset

} evals_data_cumulative <- data.table::rbindlist(df_list)

}

course_list <- unique(evals_data_df$course) results <- lapply(X = course_list,FUN = iterate) results <- data.table::rbindlist(results)

p_anim <- ggplot(data = results, aes(x = score,fill = course)) + geom_histogram(color=“black”)

anim <- p_anim + transition_manual(sample,cumulative = T) + ease_aes(“linear”) + enter_fade() + exit_fade() + theme_custom + labs(x=“Score”,y=“Count”,fill=““) + facet_wrap(~course)

anim <- animate(anim, fps=50,height = 350, width =500, renderer = gifski_renderer(loop = FALSE))